Embodiments relate to database query searching, and in particular, to search optimization using a graph community structure. Unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Database technology is evolving toward the use of in-memory column based database architectures. With such an in-memory database, large quantities of data are stored in random access memory (RAM), making that data available for rapid access and analysis for processing in response to queries posed by a database user.
However, the extremely voluminous data (e.g., possibly on the order of millions or even billions of records) present in such in-memory databases can consume large quantities of processing and memory resources. Searching of such in-memory data records in an efficient manner can significantly reduce the time and resources consumed in analyzing such large amounts of data.